Mauro Cesa
Quant finance editor
Mauro Cesa is quantitative finance editor for Risk.net, based in London. He leads the team responsible for the publication of quantitative research across all brands of the division.
The section of Risk.net he manages, Cutting Edge, publishes peer-reviewed papers on derivatives, asset and risk management, and commodities.
Mauro holds a degree in economics from the University of Trieste and a masters in quant finance from the University of Brescia.
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Articles by Mauro Cesa
Quantcast Master’s Series: Kihun Nam, Monash University
Melbourne-based programme winks at pension fund sector
Quantcast Master’s Series: Petter Kolm, Courant Institute
The NYU programme is taught almost exclusively by elite financial industry practitioners
Want to be a quant? Here’s how (and how not) to get hired
Stay curious, be a team player, speak well – and don’t be big-headed
Quantcast Master’s Series: Laura Ballotta, Bayes Business School
The business school prioritises the teaching of applicable knowledge with a keen eye on the real world
For tomorrow’s quants, Python is essential; AI isn’t
Proportion of PhDs in quant teams is sliding, as employers focus on all-round skills
Podcast: Iabichino on finance-native neural networks
UBS quant explains how to incorporate financial laws into an AI framework
Quantcast Master’s Series: Dan Stefanica and Jim Gatheral
Baruch College leaders on how they manage the top-ranked quant finance master’s programme
Tomorrow’s Quants: what it takes to be a next-gen modeller
Employers increasingly prize mix of hard and soft skills, Risk.net survey reveals
Copulas find new role in derivatives pricing
Pricing model for exotic options revives poster child of 2008 credit crisis
Lightening the RWA load in securitisations
Credit Agricole quants propose new method for achieving capital neutrality
Podcast: Muhle-Karbe on the maths behind broker selection
Imperial College’s mathematical finance head introduces new tool to measure slippage and trade quality
Podcast: Villani and Musaelian on a quantum boost for machine learning
Classical methods struggle with highly dimensional problems. Quantum cognition takes a different approach, as hedge fund duo explain